Health Care Economics: A Study Guide for Neuroradiology Fellows, Part 2

Turnaround time and efficiency of pediatric outpatient brain magnetic resonance imaging: a multi-institutional cross-sectional study

BACKGROUND

Aside from single-center reports, few data exist across pediatric institutions that examine overall MRI turnaround time (TAT) and the determinants of variability.

OBJECTIVE

To determine average duration and determinants of a brain MRI examination at academic pediatric institutions and compare the duration to those used in practice expense relative value units (RVUs).

MATERIALS AND METHODS

This multi-institutional cross-sectional investigation comprised four academic pediatric hospitals. We included children ages 0 to < 18 years who underwent an outpatient MRI of the brain without contrast agent in 2019. Our outcome of interest was the overall MRI TAT derived by time stamps. We estimated determinants of overall TAT using an adjusted log-transformed multivariable linear regression model with robust standard errors.

RESULTS

The average overall TAT significantly varied among the four hospitals. A sedated brain MRI ranged from 158 min to 224 min, a non-sedated MRI from 70 min to 112 min, and a limited MRI from 44 min to 70 min. The most significant predictor of a longer overall TAT was having a sedated MRI (coefficient = 0.71, 95% confidence interval [CI]: 0.66-0.75; P < 0.001). The median MRI scan time for a non-sedated exam was 38 min and for a sedated exam, 37 min, approximately double the duration used by the Relative Value Scale (RVS) Update Committee (RUC).

CONCLUSION

We found considerable differences in the overall TAT across four pediatric academic institutions. Overall, the significant predictors of turnaround times were hospital site and MRI pathway (non-sedated versus sedated versus limited MRI).

The Composite Severity Score for Lumbar Spine MRI: a Metric of Cumulative Degenerative Disease Predicts Time Spent on Interpretation and Reporting

Conventional measures of radiologist efficiency, such as the relative value unit, fail to account for variations in the complexity and difficulty of a given study. For lumbar spine MRI (LMRI), an ideal performance metric should account for the global severity of lumbar degenerative disease (LSDD) which may influence reporting time (RT), thereby affecting clinical productivity. This study aims to derive a global LSDD metric and estimate its effect on RT. A 10-year archive of LMRI reports comprising 13,388 exams was reviewed. Objective reporting timestamps were used to calculate RT. A natural language processing (NLP) tool was used to extract radiologist-assigned stenosis severity using a 6-point scale (0 = “normal” to 5 = “severe”) at each lumbar level. The composite severity score (CSS) was calculated as the sum of each of 18 stenosis grades. The predictive values of CSS, sex, age, radiologist identity, and referring service on RT were examined with multiple regression models. The NLP tool accurately classified LSDD in 94.8% of cases in a validation set. The CSS increased with patient age and differed between men and women. In a univariable model, CSS was a significant predictor of mean RT (R² = 0.38, p < 0.001) and independent predictor of mean RT (p < 0.001) controlling for patient sex, patient age, service location, and interpreting radiologist. The predictive strength of CSS was stronger for the low CSS range (CSS = 0–25, R² = 0.83, p < 0.001) compared to higher CSS values (CSS > 25, R² = 0.15, p = 0.05). Individual radiologist study volume was negatively correlated with mean RT (Pearson’s R =  − 0.35, p < 0.001). The composite severity score predicts radiologist reporting efficiency in LMRI, providing a quantitative measure of case complexity which may be useful for workflow planning and performance evaluation.